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Ai Platform Engineer Jobs in Arizona (NOW HIRING)

AI IAM Architect

Tempe, AZ · Remote

$153K - $255K/yr

The AI IAM Architect partners across AI/platform engineering, IAM, security, and enterprise architecture to define reusable, secure, and production-ready identity standards for agents. Key ...

Container Platform Engineer

Chandler, AZ · On-site

$105K - $138K/yr

... Platform|Terraform Technical Skills 3 Technology|Devops|Ansible Technical Skills 4 Technology|Open ... Our AI-driven solutions empower financial institutions to make smarter decisions, enhance customer ...

ABOUT THE ROLE Our Senior Media Platform Engineer role will build and operate the workflow ... Partner with AI/ML stakeholders to evaluate model options (build vs buy vs fine-tune), including ...

Preferred Skill and Experience Experience in cloud-based platforms like OpenShift, AWS, GCP, Azure ... engineering, and emerging technologies, including generative AI and agentic AI.Members of the STG ...

Preferred Skill and Experience Experience in cloud-based platforms like OpenShift, AWS, GCP, Azure ... engineering, and emerging technologies, including generative AI and agentic AI.Members of the STG ...

Principal AI Engineer

Tucson, AZ · On-site

$200 - $250/hr

This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to ...

Principal AI Engineer

Tucson, AZ · On-site

$200 - $250/hr

This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to ...

AI/ML Engineer - Remote

Phoenix, AZ · Remote

$200 - $350/hr

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

... Power Platform Engineer will design and implement enterprise-level solutions using the Power ... Experience building AI-powered solutions using Microsoft Copilot Studio and Azure OpenAI services

Showing results 41-60

Ai Platform Engineer information

See Arizona salary details

$30

$59

$88

How much do ai platform engineer jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ai platform engineer in Arizona is $59.60, according to ZipRecruiter salary data. Most workers in this role earn between $47.02 and $68.75 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Arizona?

For Ai Platform Engineer jobs in Arizona, the most frequently searched job titles are:

What cities in Arizona are hiring for Ai Platform Engineer jobs?

Cities in Arizona with the most Ai Platform Engineer job openings:

Infographic showing various Ai Platform Engineer job openings in Arizona as of August 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $123,965 per year, or $59.6 per hour.

$153K - $255K/yr

Full-time

Medical, Retirement, PTO

Re-posted 14 days ago


LPL Financial rating

7.2

Company rating: 7.2 out of 10

Based on 74 frontline employees who took The Breakroom Quiz

129th of 154 rated financial services


Job description

Where Ambition Meets Innovation

Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you'll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.

Job Overview:


We are seeking an experienced Identity and Access Management (IAM) Architect with a strong AI and agent-integration focus to lead the design, proof-of-concept (POC), and hands-on implementation of identity patterns for AI workloads, conversational agents, and AI platform integrations across the enterprise. The ideal candidate combines deep IAM architecture expertise with practical engineering skills-building POCs, configuring OAuth/OIDC flows, and partnering directly with AI engineering teams to secure agent runtimes, tool access, and human-in-the-loop experiences.

This role owns IAM architecture for AI use cases, including delegated and service-to-service access, API gateway/BFF token flows, scoped credentials, and governance alignment. You will design and validate OAuth/OIDC patterns (Auth Code + PKCE, OBO, token exchange, client credentials) across identity providers (PingOne AIC, Entra ID), gateways, and agent platforms. The AI IAM Architect partners across AI/platform engineering, IAM, security, and enterprise architecture to define reusable, secure, and production-ready identity standards for agents.

Key Responsibilities:

  • Discover AI/agent identity requirements across users, services, runtimes, tools, and APIs.

  • Assess existing SSO, MFA, federation, and API authorization models; identify gaps in delegation, token lifecycle, scopes, secrets, and auditability.

  • Design enterprise IAM patterns (user context propagation, delegation chains, BFF sessions, least-privilege access) and OAuth/OIDC client models.

  • Define standards for securing agent tools, data access, and cross-domain integrations; align to zero trust and regulatory controls.

  • Produce architecture artifacts (CAD/HLD/PSS) and reference implementations.

  • Lead and build IAM POCs (end-to-end flows, token exchange, gateway enforcement, delegated agent access).

  • Configure/test identity flows; troubleshoot tokens, scopes, and integrations.

  • Implement or guide IAM integrations across gateways, BFFs, agent orchestration, and observability.

  • Transition validated patterns to IAM engineering for production rollout.

  • Define agent identity lifecycle (registration, credential rotation, revocation, environment separation).

  • Integrate IAM across AI platform components; support CI/CD and IaC for IAM configurations.

  • Establish patterns for human-in-the-loop controls, break-glass access, and rate limiting.

  • Maintain documentation, decision records, diagrams, and runbooks.

  • Deliver POC summaries, evaluations, and implementation guidance; communicate risks and dependencies.

  • Ensure regulatory compliance; partner on threat modeling and controls (secrets, PAM, audit evidence).

  • Serve as IAM SME for AI initiatives; mentor engineers.

  • Deliver production-ready IAM patterns and reduce identity risk across AI workloads.

Requirements:

  • 10+ years in IAM, security architecture, or platform engineering with significant IAM scope.

  • 2+ years building IAM POCs and troubleshooting OAuth 2.0 / OIDC flows (Auth Code + PKCE, refresh tokens, client credentials, token exchange, OBO).

  • 2+ years with PingOne AIC and/or Microsoft Entra ID.

Core Competencies:

  • Hands-on experience designing identity for APIs, microservices, and BFF architectures.

  • Experience integrating IAM with API gateways, AI/ML platforms, and modern application stacks.

  • Strong knowledge of SAML, OAuth, OIDC, JWT, scopes, and authorization patterns.

  • Familiarity with agent/tool identity models and secure integration patterns.

  • Ability to translate AI requirements into secure identity designs; strong communication skills.

Preferences:

  • Experience delivering AI/ML agents or copilots to production.

  • Experience with SailPoint, CyberArk/Delinea, or Auth0/CIAM.

  • Knowledge of AI-aware API gateways (e.g., Kong).

  • Experience with IAM modernization or M&A programs.

  • Relevant certifications (CISSP, CCSP, Entra, Ping, SailPoint, AWS).

  • Familiarity with zero trust and identity threat detection.


Pay Range:

$153,470.00 - $255,749.00
Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play - such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!

Company Overview:

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace(6) , LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses. For further information about LPL, please visit www.lpl.com.


At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.


For further information about LPL, please visit www.lpl.com.


Join the LPL team and help us make a difference by turning life's aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.


Information on Interviews:

LPL will only communicate with a job applicant directly from an@lplfinancial.comemail address and will never conduct an interview online or in a chatroom forum. During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant's bank or credit card. Should you have any questions regarding the application process, please contact LPL's Human Resources Solutions Center at(855) 575-6947.


EAC 5.19.26


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